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Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan

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Abstract

Twitter has emerged as outstanding and most prominent social media in today’s technological age. The data proliferates in quick and words with its activities trigger get fast responses from the users. This platform is perfect for promoting political perspectives, particularly when election campaigns are on its peak. Political trends on Twitter media has been contemplated in the course of recent years. In the past research, both supervised and unsupervised methodologies have been used to analyze the Twitter trends. Most of the Tweet classification approaches utilized built in Dictionaries, Naïve Bayes, K-Nearest Neighbors (KNN), decision tree and Support Vector Machines (SVM) classifiers. However, in case of democratic election these trends can be mined to predict the winning party. However, all such approaches produce poor results due to language issues, low accuracy, limited access to internet and lower literacy rate in less developed countries such as Pakistan. This research study, find the best possible way for collection of tweets related to different political parties and build a prediction model that may analyze sentiments and opinions expressed by peoples in their Tweets. In this research work, a prediction based model along with novel similarity measure has been proposed to predict the election results of political parties in Pakistan. The proposed work is composed of data collection, preprocessing, aspect extraction, aspect refinement and final prediction using Bayesian theorem. Form the experimental results, it is concluded that proposed approach perform better than existing techniques by obtaining almost 98% accuracy and efficiently cover the limitations of existing studies.

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Authors and Affiliations

  1. University Institute of Information Technology - PMAS Arid Agriculture University, Rawalpindi, Pakistan

    Asif Nawaz, Tariq Ali, Yaser Hafeez, Saif ur Rehman & Muhammad Rizwan Rashid

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  1. Asif Nawaz
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  2. Tariq Ali
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  3. Yaser Hafeez
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  4. Saif ur Rehman
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  5. Muhammad Rizwan Rashid
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Correspondence to Asif Nawaz.

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Nawaz, A., Ali, T., Hafeez, Y. et al. Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan. Spat. Inf. Res. 30, 169–181 (2022). https://doi.org/10.1007/s41324-021-00420-7

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  • DOI: https://doi.org/10.1007/s41324-021-00420-7

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